New Technology, Human Capital and Growth in a Developing Country

In a developing country with three sectors: consumption goods, new tech- nology, and education, the productivity of the consumption goods depends on a new technology and skilled labor used to produce this new technology. There can be three stages of economic growth. In the …rst stage the country concentrates on the production of consumption goods; in the second the country must import both physical capital and new technology capital to produce consumption goods and new technology; in the third the country must import capital and invest in the training and education of high skilled labor.Optimal growth model; New technology capital;Human Capital; Developing country

New Technology, Human Capital and Growth for European Transitional Economies.

We consider a transitional country with three sectors in economy: con- sumption goods, new technology, and education. Productivity of the con- sumption goods sector depends on new technology and skilled labor used for production of the new technology. Then there might be three stages of economic growth. In the first stage the country concentrates on produc- tion of consumption goods; in the second stage the country imports both physical capital and new technology capital; in the last stage the country imports new technology capital and invests in training and education of high skilled labor in the same time.Optimal growth model, New technology capital, Human Capital, Developing country.

Asymptotic periodic solutions of differential equations with infinite delay

In this paper, by using the spectral theory of functions and properties of evolution semigroups, we establish conditions on the existence, and uniqueness of asymptotic 1-periodic solutions to a class of abstract differential equations with infinite delay of the form \begin{equation*} \frac{d u(t)}{d t}=A u(t)+L(u_t)+f(t) \end{equation*} where $A$ is the generator of a strongly continuous semigroup of linear operators, $L$ is a bounded linear operator from a phase space $\mathscr{B}$ to a Banach space $X$, $u_t$ is an element of $\mathscr{B}$ which is defined as $u_t(\theta)=u(t+\theta)$ for $\theta \leq 0$ and $f$ is asymptotic 1-periodic in the sense that $\lim\limits_{t \rightarrow \infty}(f(t+1)-$ $f(t))=0$. A Lotka-Volterra model with diffusion and infinite delay is considered to illustrate our results.Comment: 13 page

Connectedness of Vietnamese bank stock returns under the impact of the COVID-19 pandemic

The COVID-19 pandemic highlighted the sensitivity of connectedness among bank stock returns in Vietnam. The aim of this study is to examine the strength of this connectedness along with the effect of government lockdown policy and COVID-19 cases on the total connectedness index (TCI) of 16 listed banks on Vietnamese stock exchanges. They are assessed using the database of FiinPro on the banking sector between January 2020 and July 2022, Vietnam Center for Disease Control and Prevention (CDC), and The World Health Organization (WHO) on the COVID-19 pandemic, employing a time-varying-parameter vector autoregressive (TVP-VAR) connectedness framework and the conditional quantile regression model. The results show that at the firm level, there is strong interdependence among bank stock returns with the average TCI being as high as 90.66%. It is also revealed that medium and large-sized banks are receivers of shock, while smaller banks are transmitters. As far as the impact on TCI is concerned, the widespread of the pandemic with the increasing number of COVID-19 cases is significantly negative, whereas the tightening of lockdown is significantly positive. Besides, the degree of the impact varies according to the 95th, 75th, 50th and 25th levels of conditional quantile regression. Based on the study’s findings, individual investors are recommended to thoroughly analyze the connectedness of banks before making investment decisions, while bank regulators should strengthen controls on credit relationships with small banks. Regarding policy makers, it is proposed to apply flexible restrictions and short-term lockdown depending on the actual outbreak of the pandemic. AcknowledgmentThe paper was conducted within the scope of Project QG21.48 of Vietnam National University

Deep Learning-Aided Multicarrier Systems

This paper proposes a deep learning (DL)-aided multicarrier (MC) system operating on fading channels, where both modulation and demodulation blocks are modeled by deep neural networks (DNNs), regarded as the encoder and decoder of an autoencoder (AE) architecture, respectively. Unlike existing AE-based systems, which incorporate domain knowledge of a channel equalizer to suppress the effects of wireless channels, the proposed scheme, termed as MC-AE, directly feeds the decoder with the channel state information and received signal, which are then processed in a fully data-driven manner. This new approach enables MC-AE to jointly learn the encoder and decoder to optimize the diversity and coding gains over fading channels. In particular, the block error rate of MC-AE is analyzed to show its higher performance gains than existing hand-crafted baselines, such as various recent index modulation-based MC schemes. We then extend MC-AE to multiuser scenarios, wherein the resultant system is termed as MU-MC-AE. Accordingly, two novel DNN structures for uplink and downlink MU-MC-AE transmissions are proposed, along with a novel cost function that ensures a fast training convergence and fairness among users. Finally, simulation results are provided to show the superiority of the proposed DL-based schemes over current baselines, in terms of both the error performance and receiver complexity